Study on the Damage Identification of Long-span Arch Bridge Based on Support Vector Machine

LIU Chun-cheng;;LIU Jiao

Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (7) : 174-178.

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PDF(1270 KB)
Journal of Vibration and Shock ›› 2010, Vol. 29 ›› Issue (7) : 174-178.
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Study on the Damage Identification of Long-span Arch Bridge Based on Support Vector Machine

  • LIU Chun-cheng1, 2; LIU Jiao1
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Abstract

As a new machine learning algorithm, the method of Support Vector Machine(SVM) has shown its superiority of the ability of regression in the fields of damage identification. Through setting variation ratio of curvature mode to the feature parameters of damage identification, the method of the damage identification of long-span arch bridge based on SVM is presented. At first, the variation ratio of curvature mode is used to carry on damage location identification, then, the training sample is reconstructed. After that the method of least square support vector machine is used to long-span arch bridge damage extent identification, and the identification results of this method which are very close to target are obtained under the condition of small sample. To compare with results from the RBF neural network, the precision of the method in this paper is verified.

Key words

Support Vector Machine / variation ratio of curvature mode / damage identification / arch bridge / suspender

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LIU Chun-cheng;;LIU Jiao. Study on the Damage Identification of Long-span Arch Bridge Based on Support Vector Machine[J]. Journal of Vibration and Shock, 2010, 29(7): 174-178
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